One of the main challenges for road authorities is to maintain the quality of the road infrastructure. Road anomalies can have a significant impact on traffic flow, the condition of vehicles, and the comfort of occupants of vehicles. Strategies such as pavement management systems use pavement evaluation vehicles that are equipped with state-of-the-art devices to assist road authorities in identifying and repairing these anomalies. The quantity of data available is limited, however, by the limited availability and, therefore, coverage of these vehicles. To address this problem, several investigations have been conducted on the use of smartphones or equipping vehicles with additional sensors to identify the presence of road anomalies. This paper aims to add to this arsenal by using sensors already available in production vehicles to identify road anomalies. If production vehicles could be used to identify road anomalies, then road authorities would be equipped with an additional fleet of mobile sensors (vehicles traveling on a particular road) to receive initial insights into the presence of anomalies. This information could then be used to assist road authorities to deploy their staff and equipment more precisely at these locations, such that appropriate equipment reaches the right place at the right time. In this paper, an algorithm that uses lateral acceleration and individual wheel speed signals, which are commonly available vehicular variables, was developed to detect potholes using machine learning techniques. The results of the algorithm were validated with real life test scenarios.


    Access

    Download

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Investigation on Identifying Road Anomalies using In-Vehicle Sensors for Cooperative Applications and Road Asset Management


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2020-06-06




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Vehicle-road cooperative road traffic system

    ZHANG KUN / ZHU XIAOLONG / WANG HAO | European Patent Office | 2021

    Free access

    New Zealand road asset management

    McGuire, J. F. / Robertson, D. A. / McMillan, J. H. et al. | British Library Conference Proceedings | 1994


    Road Asset Management: Innovative Approaches

    Salem Al-Samahi, Soughah / Varela Soto, Fernando | Springer Verlag | 2022


    Road asset detection model construction and road asset detection method

    WEI CHUANG / SHI XIAOMENG / WEI JIANKANG et al. | European Patent Office | 2022

    Free access

    Detecting Road Anomalies

    BATTS ZACHARY THOMAS / SUN LUDONG / WOODARD KY et al. | European Patent Office | 2022

    Free access